When Values are made explicit, they provide clarity on what “good” looks like. And when they are shared, they build unity in a group. They build culture.
- Think customer first. We obsess about adding value for our customers - guests, partners, colleagues - to make it easier for everyone to experience the world.
- Own it. We deliver on our promises, make informed decisions and prioritize to get the important things done today.
- Learn forever. We are resilient, take time to reflect, and seek to learn – from colleagues, from the outside world and from our failures.
- Succeed together. We celebrate team success, through making connections, building trust and valuing the diverse perspectives of others.
- Do the right thing. We get the right results the right way. For each other, our communities and the world around us.
- Transform existing reporting and dashboard systems, streamlining and optimising them to deliver faster, clearer, and more actionable insights including supporting new experiments.
- Design, develop, and maintain comprehensive real-time dashboards and reports that track key Customer Service KPIs, ensuring data-driven decision-making at all levels.
- Apply advanced analytics techniques, including correlation and causation modeling, to accurately diagnose metric fluctuations and their impact on Customer Service operations.
- Support the CS operations and Service and Process design by unlocking trends, patterns, and root causes in operational data to proactively drive service improvements and efficiency gains.
- Deliver executive-level performance updates with actionable insights, influencing strategic decisions both within Customer Service and across the organisation.
- Design and implement VoC programs to capture feedback through multiple channels (surveys, social media, etc.) to identify pain points, and work with business leaders on opportunities for service enhancements.
- Analyse and present VoC insights to cross-functional teams and senior leadership, guiding improvements in CS operations and across the wider organisation
- Have extensive experience in Customer Insights tooling and technologies so that they can be integrated into the Customer Service environment
- Build the vision, set the strategy, and define the roadmap for data use and data engineering services within CS.
- Act as a strategic partner to senior leaders, providing data-driven insights and recommendations to support CS objectives.
- Work as part of cross-functional initiatives, workshops, and strategy sessions to translate insights into actionable strategies, focusing on customer-centric and operational improvements.
- Develop and execute a data strategy aligned with CS objectives, focusing on data quality, integrity, and security.
- Implement data governance policies within CS, standardizing data collection, storage, and usage while ensuring compliance with privacy and security standards.
- Innovate in leveraging data analytics to drive CS performance, efficiency, and growth, exploring advanced techniques (e.g., machine learning, NLP/NLG).
Machine learning/AI Partnership
- Partner closely with ML/AI and data science teams to define data requirements, validate model outputs, and integrate AI-driven insights into customer service strategies.
- Develop robust frameworks for measuring the performance, efficiency, and business impact of AI-powered solutions and automation within Customer Service.
- Identify and champion new opportunities for applying advanced analytical and machine learning/AI techniques to address customer service challenges and drive innovation.
- Lead and inspire a high-performing team of data analysts and data scientists through a period of significant transformation, redefining how data is leveraged to enhance the customer service experience.
- Shape and execute a visionary strategy for data and analytics in Customer Service, ensuring the team evolves in capabilities, tooling, and impact to drive long-term business outcomes.
- Attract, develop, and retain top-tier talent in data engineering and analytics, creating an environment that fosters innovation, excellence, and career growth within the analytics community.
- Establish best-in-class practices for analytics, modeling, and reporting, ensuring the team operates at the forefront of modern data science and engineering.
- Champion data-driven decision-making, embedding analytics deeper into customer experience strategy and influencing key business stakeholders at all levels.
- Communicate complex data insights in simple, actionable terms for stakeholders, advocating for data-driven decision-making.
- Influence and build relationships at all levels, from the Leadership Team to operational stakeholders within CS.
- Bachelor’s degree in Data Science, Statistics, Computer Science, Business Analytics, Engineering, Economics, or a related field. MBA or other advanced degree is strongly preferred, especially with a major in a quantitative discipline
- Experience:Minimum of 10 years in data analytics, data science, or business intelligence, with substantial experience in senior leadership roles (at least 3-5 years). Background in large-scale customer service environments or similar operational domains is highly desirable.
- Proven ability to deliver data-empowered strategies, complex analytics programs, and impactful business change initiatives in global organizations. Experience in driving both transformational initiatives and business-as-usual (BAU) operational improvements, demonstrating agility to manage priorities in dynamic, high-volume settings.
- Technical Mastery:Deep expertise in advanced analytics, statistical modeling, and machine learning/AI concepts as applied to customer service and business optimizationProficiency with data analytic tools and programming languages (e.g., SQL, Python, R). Skilled in data visualization technologies such as Tableau and Power BI.Experience designing, implementing, or managing VoC (Voice of Customer) programs and integrating customer insight platforms (experience with Qualtrics or equivalent technologies considered a strong plus, but not mandatory).
- Data Strategy & Governance:Demonstrated ability to define, communicate, and execute robust data strategy and governance frameworks, including data quality, integrity, privacy, and compliance.Experience partnering with ML/AI teams to set data requirements, validate model outputs, and integrate AI insights into operational workflows at scale.
- Leadership & Team Development:Track record of inspiring, building, and developing high-performing teams of senior data analysts, scientists, and craft specialists. Proven ability to nurture environments that support innovation, continuous learning, and career growth.Experience in talent and performance management, collaborating with HR and craft leaders to embed career development frameworks, mentorship programmes, and effective review cycles.
- Customer Service Domain Knowledge:Extensive familiarity with customer service strategy, operations, and experience improvement through analytics and data-driven decision-making. Prior work in omni-channel, GenAI adoption, or AI-powered customer query routing is considered highly valuable.
- Stakeholder Management & Collaboration:Strong ability to partner with senior leadership, cross-functional partners, and external vendors. Proven effectiveness in influencing and inspiring teams at all organizational levels through clear, compelling data-driven narratives.Track record of managing 3rd party software/data relationships, negotiating with external partners, and ensuring that platforms/tools align to CS goals.
- Strategic Impact & Innovation:Exceptional analytical, problem-solving, and critical-thinking skills, with a record of leveraging data to deliver measurable business outcomes.
- Strategic mindset, staying ahead of industry trends in data analytics, customer service, and AI innovation, and translating these into competitive advantages for the CS organization.
- Craft Leadership & Community Impact:Demonstrated commitment to raising the analytics craft within and beyond Customer Service, through championing best practices, sharing knowledge, coaching/mentoring, and actively contributing to the evolution of analytics frameworks, methods, and tools.
- Communication & Influence:Strong communication and presentation skills, able to simplify complex technical insights for diverse audiences, deliver executive-level reporting, and foster an analytics-led decision culture.
- Agility & Change Management:Proven ability to adapt quickly, manage priorities in changing environments (both strategic and BAU focus), and drive continuous improvement through data
- Strategic Thinking & Analytical Rigor: Ability to define the roadmap for effective data use and provide impactful business insights for CS.
- Experience with Machine Learning/AI:Strong understanding of machine learning concepts and their application in real-world business problems, particularly in customer service contexts. Familiarity with ML model evaluation metrics (e.g., precision, recall, F1-score, accuracy) and their implications for business outcomes.
- Customer-Centricity & Service Focus: Commitment to enhancing customer service through data and insights.
- Leadership, Team Development & Craft Expertise: Drive a high-performance team culture while guiding the analytics craft within Customer Service.
- Communication & Influence: Ability to translate complex data insights into simple, actionable strategies for CS stakeholders.
- Collaboration & Partnership: Building connections across departments to ensure aligned, data-driven decision-making within CS.
If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.
